H.E. Luccock said, "No one can whistle a symphony. It takes a whole orchestra to play it." This is true in all settings, including data visualization teams. As individuals, we can produce adequate dashboards for our clients. But as a team, we can build a symphony of information to help our clients make informed decisions.
Collaborating with tools like Tableau, however, is easier said than done. You can’t work in the same workbook without stepping on each other’s toes, there’s no way to see the revisions people have made (including your own), and the version control capabilities leave a lot to be desired.
What’s an analyst team to do? If you’re going to output in Tableau, you’re going to have to make an extra effort to collaborate effectively. Here are three tips that will take you a long way:
Communication can solve the majority of issues that can arise with collaboration. Communication will ensure you don’t save over each other’s work, that you’re using the correct data sources and variables, and that everyone has a task list and deadlines they can manage. So at the beginning of any project, set up some communication standards.
Here are some things to focus on:
- Make sure everyone on the project is on a team email list, Slack or Teams group, or some other communication channel—and understands the expectations around using it.
- Set up communication expectations with the client. If everyone is speaking to the client on their own, you risk requirements not being disseminated to the entire group. Instead, have a point person for client communications so that the client has one point of contact and that person gives the information to the rest of the team.
- Ensure that everyone on the team has their project requirement list and timelines. Give yourself plenty of time before the final deliverable is due to the client so you can review the workbook as a whole and ensure it is cohesive.
- Schedule regular check-ins. Depending on the project, this may be daily, once a week, or less frequently. Whatever your timeline, just be sure to get everyone together regularly to give updates and ask questions. Some issues are better handled in person than via email.
2. Set up a collaborative environment
Tools like Tableau aren’t always the most efficient for collaborating. For example, Tableau doesn’t warn a user when someone else has a workbook open and will let you edit said workbook and save the changes even if it’s open by someone else. It's too easy for work to get saved over and lost.
To set up the environment, you need to:
- Decide if you’re going to use a project management system like Jira, SmartSheets, ClickUp, Notion, or one of the many other options available. A formal project management system will help you track your team’s progress, deadlines, and requirements, and will help ensure no one gets stuck waiting on another person.
- Look into collaborative wireframing tools like Figma or Miro. These tools are meant to be collaborative; teams can go in at the same time and see each other’s changes in real time. These kinds of tools can be used to create wireframes and mock-ups as a team, and then each member can take their piece and create it in Tableau. Clients can be given access to these sites as well. Prototyping in these kind of tools is faster and will help the final product have a cohesive look and feel that the client agrees answers their questions. They also offer the ability for the analysts and clients to leave comments on what is and isn’t working for them in the prototype.
- Establish a style guide. With multiple people working on a project, you’re going to have a great diversity of thoughts and perspectives, leading to a great deliverable for the client. However, you’re also going to have a multitude of styles, from chart types to colors and fonts. If each piece of the project has a different look and feel, the result will be a disjointed dashboard that the client may find difficult to use. So start the project by establishing your style guidelines, and build in time at the end to review the dashboards against those guidelines and standardize the formatting. Prototyping first can help reduce the time it takes to bring the workbook together.
- Decide if you’re all going to work in the same workbook, or if you’re going to have each person work in separate notebooks and then combine the sheets/dashboards together. There are pros and cons to each approach. Working in the same workbook is slower, but you’ll ensure that there’s a set standard for data and variables to use, and the insights that one analyst finds may inform the piece of the puzzle you’re working on. Breaking the work into different workbooks will move the project along faster, but you risk the styles of each person’s work being different as well as not being able to see what insights your colleagues found while building their portion.
3. Agree on roles and responsibilities
As with most group projects, the work will need to be divided up, but ultimately there will be one point person who is responsible for ensuring that all aspects of the project happen without a hitch. This person will also be the point of contact with the client.
It’s important that the team is in agreement on who is in this role, and that the person in this role understands the expectations. It’s also important that each person on the team understands the contribution they are responsible for making, so everyone helps earn the A.
By having these conversations up front, you can avoid many collaboration pitfalls and have a fun, rewarding experience working with colleagues to create a dashboard masterpiece for your client.
Collaboration is Easier with Mighty Canary
As a data analyst, you have a choice. You can create collaborative processes from scratch yourself, or you can use a tool like Mighty Canary to do it for you. What if you could communicate with your team, operate on shared best practices, and track changes automatically?
Mighty Canary can help you be more collaborative as a data team. Let our tools help you work together more seamlessly so you can work on the fun parts! Learn more>
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